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20152022
most citedTwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs

18 citations · 40 across the 11 of their papers we have counts for

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10 papers · 1 filter

cs.CL2022★ 2 cited

Cultural Re-contextualization of Fairness Research in Language Technologies in India

Shaily Bhatt, Sunipa Dev, Partha Talukdar +2

Recent research has revealed undesirable biases in NLP data and models. However, these efforts largely focus on social disparities in the West, and are not directly portable to oth…

cs.CL2022★ 3 cited

UGIF: UI Grounded Instruction Following

Sagar Gubbi Venkatesh, Partha Talukdar, Srini Narayanan

Smartphone users often find it difficult to navigate myriad menus to perform common tasks such as "How to block calls from unknown numbers?". Currently, help documents with step-by…

cs.CL2022★ 18 cited

TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs

Aditya Sharma, Apoorv Saxena, Chitrank Gupta +3

Recent years have witnessed much interest in temporal reasoning over knowledge graphs (KG) for complex question answering (QA), but there remains a substantial gap in human capabil…

cs.CL2022★ 7 cited

Re-contextualizing Fairness in NLP: The Case of India

Shaily Bhatt, Sunipa Dev, Partha Talukdar +2

Recent research has revealed undesirable biases in NLP data and models. However, these efforts focus on social disparities in West, and are not directly portable to other geo-cultu…

cs.CL2022★ 4 cited

Evaluating the Diversity, Equity and Inclusion of NLP Technology: A Case Study for Indian Languages

Simran Khanuja, Sebastian Ruder, Partha Talukdar

In order for NLP technology to be widely applicable, fair, and useful, it needs to serve a diverse set of speakers across the world's languages, be equitable, i.e., not unduly bias…

cs.CL2021★ 1 cited

OKGIT: Open Knowledge Graph Link Prediction with Implicit Types

Chandrahas, Partha Pratim Talukdar

Open Knowledge Graphs (OpenKG) refer to a set of (head noun phrase, relation phrase, tail noun phrase) triples such as (tesla, return to, new york) extracted from a corpus using Op…

cs.CL2021★ 1 cited

MergeDistill: Merging Pre-trained Language Models using Distillation

Simran Khanuja, Melvin Johnson, Partha Talukdar

Pre-trained multilingual language models (LMs) have achieved state-of-the-art results in cross-lingual transfer, but they often lead to an inequitable representation of languages d…

cs.CL2021

Reordering Examples Helps during Priming-based Few-Shot Learning

Sawan Kumar, Partha Talukdar

The ability to learn from limited data, or few-shot learning, is a desirable and often critical requirement for NLP systems. While many existing methods do poorly at learning from…

cs.CL2017

Higher-order Relation Schema Induction using Tensor Factorization with Back-off and Aggregation

Madhav Nimishakavi, Partha Talukdar

Relation Schema Induction (RSI) is the problem of identifying type signatures of arguments of relations from unlabeled text. Most of the previous work in this area have focused onl…

cs.CL2015★ 2 cited

Want Answers? A Reddit Inspired Study on How to Pose Questions

Danish, Yogesh Dahiya, Partha Talukdar

Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information…